Data Analyst

PSD Group; Barcelona; Presencial; EUR 45.000 - 65.000; Jornada completa

Descripción de la vacante

PSD Group, a global technology organisation, is seeking a Data Cleansing & Migration Analyst to support data quality, transformation and migration within a large ERP transformation programme. You will partner with Data Owners and stakeholders to ensure data accuracy and integrity across the migration lifecycle.

The role requires hands-on analysis, cleansing, and validation of both structured and unstructured data, development of data quality dashboards, and documentation of data rules within the

Formación

• Minimum 5 years' experience in data analysis, data manipulation, data migration, or a related data-focused role.
• Experience with SQL, PowerBI, and data query tools.
• Strong understanding of data quality, data transformation, and data governance principles.
• Excel skills, including complex formulas, data modelling, reconciliation, and large dataset analysis.
• Experience using Microsoft Copilot or similar AI-enabled productivity tools, with the ability to independently review, validate, and challenge outputs.

Responsabilidades

• Extract, analyse, and manipulate data to support data quality assessments, cleansing initiatives, and migration activities.
• Review data objects and datasets, applying analytical thinking and best practice methodologies to identify issues and recommend data quality criteria.
• Develop and maintain manual data quality dashboards in Excel, transitioning to automated reporting solutions as they become available.
• Draft business glossaries and support the maintenance of data quality management tools and documentation.
• Work closely with Data Owners, Data Stewards, and business stakeholders to identify data gaps and opportunities for improving data quality.
• Support ongoing data cleansing activities by analysing, validating, and reconciling data across multiple domains.
• Define additional validation checks, metrics, and quality controls as data quality matures throughout the programme.
• Assist in the implementation of automated dashboards and document data quality rules, standards, and criteria within the data management framework.
• Support data mapping, transformation, and migration activities across the ERP programme.
• Maintain comprehensive documentation and audit trails for all migration-related activities.
• Ensure data transformation processes are accurately documented and compliant with programme governance and audit requirements.
• Assist with data validation, reconciliation, and issue resolution throughout testing and migration cycles.

Conocimientos

SQL

PowerBI

Excel

Data analysis

Data migration

Data governance

AI tools (Copilot)

Stakeholder communication

Herramientas

Data modelling tools

Descripción del empleo

Our client is a global technology organisation supporting the air transport industry through the delivery of mission-critical IT and communication solutions.

As part of a major ERP transformation programme, they are seeking a Data Cleansing & Migration Analyst to support data quality, transformation, and migration activities across the programme.

About the Role

The Data Cleansing & Migration Analyst will play a key role in supporting data quality improvement, data transformation, and migration activities within a large-scale ERP programme. Working closely with business stakeholders and the wider Data Team, the successful candidate will be responsible for analysing, validating, cleansing, and transforming data to ensure accuracy and integrity throughout the migration lifecycle.

Key Responsibilities:

Data Cleansing & Quality

• Extract, analyse, and manipulate data to support data quality assessments, cleansing initiatives, and migration activities.
• Review data objects and datasets, applying analytical thinking and best practice methodologies to identify issues and recommend data quality criteria.
• Develop and maintain manual data quality dashboards in Excel, transitioning to automated reporting solutions as they become available.
• Draft business glossaries and support the maintenance of data quality management tools and documentation.
• Work closely with Data Owners, Data Stewards, and business stakeholders to identify data gaps and opportunities for improving data quality.
• Support ongoing data cleansing activities by analysing, validating, and reconciling data across multiple domains.
• Define additional validation checks, metrics, and quality controls as data quality matures throughout the programme.
• Assist in the implementation of automated dashboards and document data quality rules, standards, and criteria within the data management framework.

ERP Data Migration & Transformation

• Support data mapping, transformation, and migration activities across the ERP programme.
• Maintain comprehensive documentation and audit trails for all migration-related activities.
• Ensure data transformation processes are accurately documented and compliant with programme governance and audit requirements.
• Assist with data validation, reconciliation, and issue resolution throughout testing and migration cycles.

What we are looking for

Skills & Experience Required:

• Minimum 5 years' experience in data analysis, data manipulation, data migration, or a related data-focused role.
• Experience with SQL, PowerBI, and data query tools.
• Strong understanding of data quality, data transformation, and data governance principles.
• Excel skills, including complex formulas, data modelling, reconciliation, and large dataset analysis.
• Experience using Microsoft Copilot or similar AI-enabled productivity tools, with the ability to independently review, validate, and challenge outputs.
• Strong analytical skills with the ability to transform, map, validate, and assess data accurately and securely.
• Experience working with structured and unstructured datasets within complex business environments.
• Excellent attention to detail and ability to maintain high levels of accuracy across large volumes of data.
• Strong communication and stakeholder engagement skills.